Q-omics provides the consensus-scored ECRG4 profile across patient tissues and cancer cell-line models. ECRG4 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ECRG4 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, ECRG4 RNA expression shows 17,338 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, and LUAD as cancer lineages where ECRG4 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for ECRG4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ECRG4 survival associations across molecular data types. ECRG4 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ECRG4 RNA expression–survival associations across cancer types. High ECRG4 expression shows unfavorable associations in BLCA and LGG, but favorable associations in KIRC, BRCA, LIHC and LUAD. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for ECRG4 RNA expression.
This table summarizes ECRG4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for ECRG4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ECRG4 shows lower tumor expression in KIRC, HNSC, BLCA, KIRP, LUAD and COAD. The KIRC box plot shows higher ECRG4 RNA expression in normal versus tumor tissue (log2 FC = −2.641, t-test p < 0.001).
This table shows molecular features associated with ECRG4 in patient tissues and cancer cell lines. In patient samples, ECRG4 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, ECRG4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_NSCLC_LUSC.
